Interacting default intensity with a hidden Markov process

Feng Hui Yu, Wai Ki Ching*, Jia Wen Gu, Tak Kuen Siu

*Corresponding author for this work

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this paper we consider a reduced-form intensity-based credit risk model with a hidden Markov state process. A filtering method is proposed for extracting the underlying state given the observation processes. The method can be applied to a wide range of problems. Based on this model, we derive the joint distribution of multiple default times without imposing stringent assumptions on the form of default intensities. Closed-form formulas for the distribution of default times are obtained which are then applied to solve a number of practical problems such as hedging and pricing credit derivatives. The method and numerical algorithms presented can be applicable to various forms of default intensities.

Original languageEnglish
Pages (from-to)781-794
Number of pages14
JournalQuantitative Finance
Volume17
Issue number5
Early online date7 Nov 2016
DOIs
Publication statusPublished - 4 May 2017

Keywords

  • Credit derivatives
  • Default risk
  • Hidden Markov model (HMM)
  • Reduced-form intensity model

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